Bayesian blind component separation for cosmic microwave background observations

2002 ◽  
Author(s):  
H. Snoussi
Keyword(s):  
Cosmic Microwave Background ◽  
Component Separation ◽  
Microwave Background

scholarly journals BAYESIAN COMPONENT SEPARATION AND COSMIC MICROWAVE BACKGROUND ESTIMATION FOR THE FIVE-YEARWMAPTEMPERATURE DATA

2009 ◽  
Vol 705 (2) ◽  
pp. 1607-1623 ◽  
Author(s):  
C. Dickinson ◽  
H. K. Eriksen ◽  
A. J. Banday ◽  
J. B. Jewell ◽  
K. M. Górski ◽  
...  
Keyword(s):  
Cosmic Microwave Background ◽  
Component Separation ◽  
Microwave Background ◽  
Background Estimation

scholarly journals Accelerating linear system solvers for time-domain component separation of cosmic microwave background data

2020 ◽  
Vol 638 ◽  
pp. A73
Author(s):  
J. Papež ◽  
L. Grigori ◽  
R. Stompor
Keyword(s):  
Cosmic Microwave Background ◽  
Time Domain ◽  
Component Separation ◽  
Microwave Background ◽  
Data Set ◽  
Background Data ◽  
Cosmic Microwave Background Data ◽  
Subspace Recycling ◽  
The Time Domain ◽  
Sampling Procedures

Component separation is one of the key stages of any modern cosmic microwave background data analysis pipeline. It is an inherently nonlinear procedure and typically involves a series of sequential solutions of linear systems with similar but not identical system matrices, derived for different data models of the same data set. Sequences of this type arise, for instance, in the maximization of the data likelihood with respect to foreground parameters or sampling of their posterior distribution. However, they are also common in many other contexts. In this work we consider solving the component separation problem directly in the measurement (time-) domain. This can have a number of important benefits over the more standard pixel-based methods, in particular if non-negligible time-domain noise correlations are present, as is commonly the case. The approach based on the time-domain, however, implies significant computational effort because the full volume of the time-domain data set needs to be manipulated. To address this challenge, we propose and study efficient solvers adapted to solving time-domain-based component separation systems and their sequences, and which are capable of capitalizing on information derived from the previous solutions. This is achieved either by adapting the initial guess of the subsequent system or through a so-called subspace recycling, which allows constructing progressively more efficient two-level preconditioners. We report an overall speed-up over solving the systems independently of a factor of nearly 7, or 5, in our numerical experiments, which are inspired by the likelihood maximization and likelihood sampling procedures, respectively.

scholarly journals Impact of polarised extragalactic sources on the measurement of CMB B-mode anisotropies

2020 ◽  
Vol 642 ◽  
pp. A232 ◽  
Author(s):  
G. Lagache ◽  
M. Béthermin ◽  
L. Montier ◽  
P. Serra ◽  
M. Tucci
Keyword(s):  
Cosmic Microwave Background ◽  
Shot Noise ◽  
Large Scale ◽  
Power Spectra ◽  
Frequency Component ◽  
Component Separation ◽  
Complete Analysis ◽  
Microwave Background ◽  
Small Aperture ◽  
Infrared Background

One of the main goals of cosmology is to search for the imprint of primordial gravitational waves in the polarisation filed of the cosmic microwave background to probe inflation theories. One of the obstacles in detecting the primordial signal is that the cosmic microwave background B-mode polarisation must be extracted from among astrophysical contaminations. Most efforts have focus on limiting Galactic foreground residuals, but extragalactic foregrounds cannot be ignored at the large scale (ℓ ≲ 150), where the primordial B-modes are the brightest. We present a complete analysis of extragalactic foreground contamination that is due to polarised emission of radio and dusty star-forming galaxies. We update or use current models that are validated using the most recent measurements of source number counts, shot noise, and cosmic infrared background power spectra. We predict the flux limit (confusion noise) for future cosmic microwave background (CMB) space-based or balloon-borne experiments (IDS, PIPER, SPIDER, LiteBIRD, and PICO), as well as ground-based experiments (C-BASS, NEXT-BASS, QUIJOTE, AdvACTPOL, BICEP3+Keck, BICEPArray, CLASS, Simons Observatory, SPT3G, and S4). The telescope aperture size (and frequency) is the main characteristic that affects the level of confusion noise. Using the flux limits and assuming mean polarisation fractions independent of flux and frequency for radio and dusty galaxies, we computed the B-mode power spectra of the three extragalactic foregrounds (radio source shot noise, dusty galaxy shot noise, and clustering). We discuss their relative levels and compare their amplitudes to that of the primordial tensor modes parametrised by the tensor-to-scalar ratio r. At the reionisation bump (ℓ = 5), contamination by extragalactic foregrounds is negligible. While the contamination is much lower than the targeted sensitivity on r for large-aperture telescopes at the recombination peak (ℓ = 80), it is at a comparable level for some of the medium- (∼1.5 m) and small-aperture telescope (≤0.6 m) experiments. For example, the contamination is at the level of the 68% confidence level uncertainty on the primordial r for the LiteBIRD and PICO space-based experiments. These results were obtained in the absence of multi-frequency component separation (i.e. considering each frequency independently). We stress that extragalactic foreground contaminations have to be included in the input sky models of component separation methods dedicated to the recovery of the CMB primordial B-mode power spectrum. Finally, we also provide some useful unit conversion factors and give some predictions for the SPICA B-BOP experiment, which is dedicated to Galactic and extragalactic polarisation studies. We show that SPICA B-BOP will be limited at 200 and 350 μm by confusion from extragalactic sources for long integrations in polarisation, but very short integrations in intensity.

Cosmic Microwave Background Component Separation by Parameter Estimation

2006 ◽  
Vol 641 (2) ◽  
pp. 665-682 ◽  
Author(s):  
H. K. Eriksen ◽  
C. Dickinson ◽  
C. R. Lawrence ◽  
C. Baccigalupi ◽  
A. J. Banday ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Cosmic Microwave Background ◽  
Component Separation ◽  
Background Component ◽  
Microwave Background
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